PGPB and/or AM Fungi Consortia Affect Tomato Native Rhizosphere Microbiota

Tomatoes are one of the most important crops worldwide and also play a central role in the human diet. Microbial consortia are microorganism associations, often employed as bioinoculants, that can interact with the native rhizosphere microbiota. The aim of this study was to evaluate the impact of a bacterial-based biostimulant (Pseudomonas fluorescens and Bacillus amyloliquefaciens) (PSBA) in combination, or not, with a commercial inoculum Micomix (Rhizoglomus irregulare, Funnelliformis mosseae, Funnelliformis caledonium, Bacillus licheniformis, Bacillus mucilaginosus) (MYC) on the native rhizosphere communities and on tomato production. The trial was carried out using Solanum lycopersicum in an open field as follows: control full NPK (CFD), control reduced NPK (CRD), MYC, PSBA, PSBA + MYC. Bacterial population in the different samples were characterized using a next generation sequencing approach. The bioinocula effect on the native rhizosphere microbiota resulted in significant variation both in alpha and beta diversity and in a specific signature associated with the presence of biostimulants, especially in the presence of co-inoculation (PSBA + MYC). In particular, the high initial biodiversity shifts in the community composition occurred and consisted in the increase in the abundance of genera correlated to the soil acidification and in an enhanced density of nitrogen-fixing microbes. The results also highlighted the well-known rhizosphere effect.


Introduction
The commonly cultivated tomato (Solanum lycopersicum L.) is an annual crop originating from the Andes region in South America, and has gained a significant spot in the vegetable crop production worldwide. Second only to potatoes, the global production of tomatoes in 2021 was more than 189 million tons, distributed in 5 Mha, where 80% of this value is intended for industrial transformation [1,2]. Italy is the first European producer, with 6.6 million tons produced in almost 100 kha, mainly in the Southern Italy [2,3].
Besides the importance in the overall vegetable crop cultivation, tomatoes also have a central function in the human diet. They are rich in antioxidants [4] with beneficial properties from anticancer and immune boosting responses to bowel disease amelioration [1]. Considering the constant intensification of agricultural practices and artificial selection, tomato plants are more susceptible to soil borne diseases due to their genetic homogeneity [5,6], and the adverse effects caused by climate change are adding more threats to the tomato yields [3,7]. In this scenario, more sustainable but effective agricultural practices are needed, especially to ensure food supplies for a constantly growing population [8,9].
The soil microbiota harbors a multitude of organisms (e.g., viruses, archaea, bacteria, lower and higher eukaryotes) that are deeply influenced by both biotic and abiotic factors. Their interactions with plants' radical apparatus have an effect on different agricultural aspects, such as plant overall health, yield production and fruit quality [8,10,11]. Considering their explicated positive impacts, microbial consortia, which are associations of microorganisms with non-conflicting relationships, are often employed as bioinoculants in a wide variety of crops. These inocula can interact with the native rhizosphere microbiota and influence the "rhizosphere feedback loop" [11]. Two main functional groups interact closely with crops showing their beneficial roles: plant growth promoting bacteria (PGPB) and arbuscular mycorrhizal fungi (AMF).
PGPB refer to a comprehensive set of bacterial genera that interrelate with crops, explicating both direct and indirect mechanisms that can boost the plant fitness by providing nutrients otherwise unavailable to roots, affecting the morphology and biomass and resistance to phytopathogens and abiotic stresses [5,11].
AMF are obligate symbiotic microorganisms belonging to the subphylum Glomeromycotina and are able to establish relationships with plants [12]. These fungi are able to produce an extraradical mycelium that improves the plant's uptake of phosphorus and nitrogen [13]. Moreover, AM symbiosis can induce tolerance to various biotic and abiotic stresses [14,15] and modulate the secondary metabolism of the plant, also improving the plant fruit production and the fruit quality in terms of sugar and vitamin content [16,17].
Although the use of microbiota consortia has some limitations (i.e., interspecific competition, EU regulation on bioinocula, etc.), they are currently one of the research areas in sustainable agriculture with larger investments [18]. Furthermore, the possible bioinocula effect on the native microbiota community is well summarized in the review by Vuolo et al. [11] but is still poorly investigated, especially under real field conditions.
In tomato crops, soil bioinoculation has been reported to influence various aspects. Considering the PGPB inoculation, several bacterial strains have been shown to be involved in promoting tomato plant growth, improving yield and protecting against pathogens [19,20]. Zuluaga et al. [21] found that inoculation with different beneficial bacterial strains resulted in a shift in root metabolomics, with a consequent chemotaxis of beneficial bacteria leading to an improvement in tomato growth and biomass. Moreover, an initial strong microbiota has been shown to be essential for plant protection against pathogens with the presence of PGBP, such as Pseudomonas and Bacillus correlated with healthier plants [22], while different plant growth-promoting rhizobacteria have the ability to reprogram defenserelated metabolism [23].
Regarding the beneficial effect of AM fungi in tomato roots, their presence is associated with a better uptake of substances, both spatially, through the formation of an extraradical micelium, and temporally, as AM fungi can guarantee a better nutritional status in the long term [24]. Furthermore, the presence of mycorrhizal fungi is associated with higher fruit quality, even when cultivated under conditions of nutrient scarcity [25] or high salinity [26]. Inoculation with AM fungi has also been correlated with a reduction in the severity of infection by pathogens such as Phytophthora nicotianae [14].
The effects of a mixed inoculation approach (PGPB + AMF) have been described by several authors as being more active to the single-kingdom inoculum. The application of bacterial and fungal biostimulants has been reported to reduce the incidence of Fusarium oxysporum f. sp. lycopersici (FOL) in tomato plants grown under controlled conditions compared to unmixed inocula [27]. The effects of mixed inocula are correlated with increased numbers, biomass and quality of tomato fruits, both under real agro-system conditions and under reduced fertilization conditions [28,29]. Furthermore, mixed inocula of fungi and phosphate-solubilising bacteria, combined with phosphorus-rich substrate, improved plant growth and yields while allowing for a reduction in fertilizer use and costs [30].
While many studies focus on the direct effects of soil bioinoculants on tomato crops, there is a gap on the combined effects of bioinoculants on plant productivity and simultaneously on the native rhizosphere microbiota, especially along the successional phenological phases. The aim of this study was to determine the impact of the addition of different types of bioinocula on the native resident microbiota in the tomato rhizosphere while subsequently describing the possible interactions that can be established between soil microorganisms and how they translate into positive effects for the plant, considering two different phenological states of tomato crop cultivation.
The trial was carried out using S. lycopersicum var. Big Rio, a processing tomato variety, in an open field in Landlab (Landlab srl Società Benefit, Quinto Vicentino (VI), Italy, 45.57 • N, 11.62 • E, 33 m a.s.l.). A permeable mulch was used to decrease weed proliferation and reduce water loss by evaporation. Irrigation was performed by drip irrigation and was supplied according to plants' demand. A hailstorm net was provided to protect the plants from possible adverse weather conditions. Nutrients were provided by basal dressing and fertigation. A reduction in NPK supply was performed on treated entries, buffers and the "CRD, reduced NPK". The products were applied at planting (0 days after planting (DAP)) and at 20 DAP.
Conventional fertilization (CFD) consisted of a base dressing before transplanting, with N (45 kg/ha), P 2 O 5 (70 kg/ha) and K 2 O (72 kg/ha) and for the entire growing period

Microbial Community Characterization
The metagenomic workflow was carried out according to Bona et al. [31]. Briefly, total genomic DNA was extracted by DNeasy ® PowerSoil ® Kit (Qiagen, Hilden, Germany) using 0.25 g of soil following the manufacturer's instructions. DNA of each sample was quantified by fluorimetric method according to the Qubit ® 2.0 Fluorimeter protocol.

Bioinformatic and Statistical Analyses
First, fastq file elaboration consisting of base calling, demultiplexing and adapter masking was performed with Illumina BCL Convert v3.9.31. Then, a clipping routine was applied to remove low-quality bases. Reads were then retained if they maintained a minimum length of 200 bp. Following the QIIME pipelines, the USEARCH algorithm (version 8.1.1756, 32-bit) allowed the following steps: chimera filtering, grouping of replicate sequences, sorting sequences per decreasing abundance and OTU identification. The operational taxonomic unit (OTU) picking aims to group query sequences into clusters, represented by centroids. Each centroid shares a level of similarity with its member sequences. An open-reference algorithm was used as a default approach unless differently enquired. All reads are used in the analysis if they maintain a minimum length of 200 bp after the removal of primer sequences and low-quality bases. Paired reads with permissive overlap at their 3 feet ends are merged into a single fragment and used as such to improve assignment accuracy. Reads that do not support overlap were maintained in the pool for downstream processing.
In an open reference analysis, sequences not matching any reference sequence of the database constitute a novel OTU and the most abundant and long read in each OTU was selected as the representative sequence. OTUs were built de novo with a clustering threshold set at 97%, with sequences that passed a pre-filter step for minimum identity of 90% with any sequence present in the reference database. OTUs in open reference analysis were generated with a minimum of 2 sequenced fragments. The RDP classifier and reference database were used to assign taxonomy with a minimum confidence threshold of 0.50. The Silva138 database was employed as 16S rDNA sequence reference.
After this elaboration, statistical analyses were performed using MicrobiomeAnalyst. First, data filtering was used to identify and remove features having low count and variance based on their abundance levels (minimum counts 30) across samples (prevalence). The statistical analysis regarding the biodiversity inside and between the different microbial populations was performed using "label" (e.g., CFD_t1; CFD_t2, etc.), "time" (t0, t1, t2) and "treatment" (CFD, CRD, etc.) as factors by considering: i) alpha diversity, characterized by the total number of observed species, Shannon and Simpson indexes, performed using the phyloseq package [32] and ii) beta diversity performed using the phyloseq package [32]. The distance between samples was measured using Bray-Curtis distance, and principal coordinate analysis (PCoA) was used to visualize the matrix in a 2D plot, where each dot represents the entire microbiome of a single sample. In this analysis, the statistical significance of the clustering pattern in ordination plots can be evaluated using permutational ANOVA (PERMANOVA).
Finally, the linear discriminant analysis effect size (LDA-LEfSe) method was applied at the genus level to identify the signature associated with the different parameters. This method is specifically designed for biomarker discovery and explanation in highdimensional metagenomic data [33]. It incorporates statistical significance with biological consistency (effect size) estimation. It performs the non-parametric factorial Kruskal-Wallis (KW) rank-sum test to identify species with significant differential abundance with regard to the factor of interest, followed by linear discriminant analysis (LDA) to calculate the effect size of each differentially abundant feature. The result consists of all the genera with the highest mean and the logarithmic LDA score (effect size). Features are considered significant based on their adjusted p-value. The default p-value cutoff was 0.05.

Root AM Colonization Assessment
Mycorrhizal colonization was assessed starting from a sample of 40 randomly chosen 1 cm long root pieces for each plant. These root samples were cleared in 10% KOH for 45 min at 60 • C, stained with 1% methyl blue in lactic acid and mounted on a slide. Mycorrhizal colonization was estimated according to Trouvelot and coworkers [34]: frequency of mycorrhization (F%), mycorrhizal degree (M%), frequency of arbuscules (A%) and frequency of vesicles (V%) were calculated. Data were statistically analyzed by one-way ANOVA (using "label" as factor) followed by Tukey HSD post hoc test with Bonferroni adjusted p-values. A two-way ANOVA was also performed using "time" and "treatment" as factors. Differences were considered significant for p-values < 0.05.

Soil Analysis
The physical-chemical analyses of the soil were performed on the samples collected at the baseline conditions, and the characteristics are reported in Table 1. Considering the parameters of soil fertility, pH was found to be 8.29, classifying the soil as alkaline. The electrical conductivity (EC) was low. The active lime was in the reference ranges (1.93%), while the available phosphorus was reported as low (19.3).
The measure of organic matter and total nitrogen are in the reference ranges (1.69 and 1.038, respectively), while the C/N ratio was 9.44, slightly lower than to the standard values. Compared to the micronutrient elements, boron quantity resulted low (<0.50), while the values of iron, manganese, and copper were higher than the reference ranges. Only zinc presented values in the standard intervals.
For the exchange complexes, exchangeable sodium and potassium showed very low and low quantities, respectively, while ion calcium was listed as very high. Ion magnesium had a normal value of 2.39. Base saturation and CEC were, respectively, normal and very high compared to the reference ranges.

Production
The CRD treatment showed 60% lower production ( Table 2), in terms of marketable fruits compared to CFD, although this difference is not statistically significant. However, if all the production is considered (marketable + green fruits), the difference is significant ( Table 2). All the treatments performed better than the CRD (from +13.1% to +60.1%) and showed a lower percentage of BER fruits.

Soil Microbiota Profiling
A total of 133,072,948 reads were obtained with a mean value of 1,073,169 reads per sample. The genomic sequences were included in the BioProject PRJNA916628, titled "Impact of PGPB bacteria and AM fungi inocula on resident communities associated with tomato roots", available in NCBI database https://submit.ncbi.nlm.nih.gov/subs/sra/SUB12451409/ overview, accessed on 20 December 2022. The BioProject contains 122 objects.  Considering the label factor (each biological treatment at each time considered), all analyzed populations showed a higher number of observed species than at baseline (t0), i.e., soil-associated microbial populations in the absence of the tomato plants ( Figure 2A). The Shannon index had very high values, ranging from 5.0 to 5.2 ( Figure 2B), with signifi-cant differences compared to the different experimental conditions. The same trend was observed also for the Simpson index, but without significant differences with respect to the label factor ( Figure 2C) with values near one, which is the maximum value that can be reached by this index.
Microorganisms 2023, 11, x FOR PEER REVIEW 10  p-value cut-off for significance is 0.05. In the figure, black diamond indicated the mean value while the black line inside the box represented the median value. Alpha diversity analysis was performed using the phyloseq package of MicrobiomeAnalyst.
Considering the time factor, populations at sampling times t1 (at the beginning of flowering) and t2 (at fruit setting) showed a higher number of observed species than at baseline (t0), with a high significant difference (p-value < 0.0001). Moreover, t1 and t2 populations were characterized by a comparable number of species ( Figure 3A). Both Shannon ( Figure 3B) and Simpson ( Figure 3C) indexes had very high values without significant differences between times. Considering the label factor (each biological treatment at each time considered), all analyzed populations showed a higher number of observed species than at baseline (t0), i.e., soil-associated microbial populations in the absence of the tomato plants ( Figure 2A). The Shannon index had very high values, ranging from 5.0 to 5.2 ( Figure 2B), with significant differences compared to the different experimental conditions. The same trend was observed also for the Simpson index, but without significant differences with respect to the label factor ( Figure 2C) with values near one, which is the maximum value that can be reached by this index.
Considering the time factor, populations at sampling times t1 (at the beginning of flowering) and t2 (at fruit setting) showed a higher number of observed species than at

Beta Diversity
Beta diversity underlines the degree of distance between the different analyzed groups, giving a measure of comparison between bacterial communities. We estimated the beta diversity according to labels ( Figure 5A), time ( Figure 5B), and treatment ( Figure 5C).
populations showing the highest values for the Shannon and Simpson indices were those combined with the presence of uninoculated plants (CFD and CRD). Moreover, a decreasing trend of the biodiversity values in the presence of fungal (MYC) or bacterial (PSBA) inoculation, and even more in the combined inoculation (PSBA + MYC) treatment, was observed ( Figure 4B,C).

Beta Diversity
Beta diversity underlines the degree of distance between the different analyzed groups, giving a measure of comparison between bacterial communities. We estimated the beta diversity according to labels ( Figure 5A), time ( Figure 5B), and treatment ( Figure  5C).  Principal coordinate analysis (PCoA) based on Bray-Curtis metrics revealed that populations were different according to label, time, and treatment factors, showing a high diversity in the genus members of the soil communities. As already highlighted in the alpha diversity analysis, the baseline microbiota showed a higher degree of dissimilarity compared to the other groups. However, a core microbiota is recognizable considering all the tested parameters.
Considering not only the presence of the tomato plant, but also the phenological state (flowering and fruit ripening, Tables 4 and 5, no significant genera were associated with the phenological shift.

Signature Associated with the Biostimulant Treatment
The results of the significant genera determining the variation of the microbial communities associated with the different biostimulant treatments are presented in Tables 6-10. Comparing the microbial communities associated to the different biological treatments to CRD (without any bioinocula), it is possible to highlight that some genera were significantly enhanced: Alsobacter, Aminobacter, Leptolyngbya EcFYyyy00, Luteitalea, Nakamurella, Rhodocytophaga, Skermanella. On the other hand, some genera seemed to be reduced compared to the CRD treatment, such as Acidibacter, Altererythrobacter, Bradyrhizobium, Chloroflexus, Cupriavidus, Devosia, Fictibacillus, Hirschia, Ideonella, Luteolibacter, Mesorhizobium, Ohtaekwangia, Promicromonospora, Pseudoflavitalea, Pseudoxanthomonas, Sorangium, Sphingopyxis, Streptomyces, and Tahibacter.

Mycorrhization Degree
The mycorrhizal colonization of the inoculated tomato plant roots after 1 and 2 months of growth is shown in Figure 6.

Mycorrhization Degree
The mycorrhizal colonization of the inoculated tomato plant roots after 1 and 2 months of growth is shown in Figure 6. Although uninoculated, the plants in CFD and CRD treatments showed a mycorrhization degree (M%) of 3.77 and 7.25, respectively. The other myc treatments (MYC and PSBA + MYC) showed similar M% (6.15 and 12.19, respectively). The other considered parameters (F %, A %, and V%) showed a similar trend. The bacterial PSBA inoculum did not affect root colonization. Evaluating the two-way ANOVA, Time could be considered the factor influencing all the analyzed parameters.

Discussion
The aim of the research presented in this paper was to evaluate the application of a bacterial-based biostimulant (P. fluorescens and B. amyloliquefaciens) in combination, or not, with the commercial inoculum Micomix and to assess the impact that these administered microorganisms have on the native microbial populations in the soil and on the production of tomatoes. Fertilization reduction induces a loss in overall production (considering marketable fruits) although the difference is not significant, but it is a significant reduction if considering marketable and non-marketable fruits. However, the addition of the inocula partially restored the production rate. This finding is in line with what has been previously reported in the literature [29] and underlines how the nutrient solubilization action operated by microorganisms improves plant nutrition, and thus, its production performance, as well. BER (blossom-end rot) is a physiological disorder usually correlated with a lack of calcium in the plant that may be due to low calcium levels in the soil, or it occurs when there are wide fluctuations in soil moisture, and the plant's ability to take up Although uninoculated, the plants in CFD and CRD treatments showed a mycorrhization degree (M%) of 3.77 and 7.25, respectively. The other myc treatments (MYC and PSBA + MYC) showed similar M% (6.15 and 12.19, respectively). The other considered parameters (F %, A %, and V%) showed a similar trend. The bacterial PSBA inoculum did not affect root colonization. Evaluating the two-way ANOVA, Time could be considered the factor influencing all the analyzed parameters.

Discussion
The aim of the research presented in this paper was to evaluate the application of a bacterial-based biostimulant (P. fluorescens and B. amyloliquefaciens) in combination, or not, with the commercial inoculum Micomix and to assess the impact that these administered microorganisms have on the native microbial populations in the soil and on the production of tomatoes. Fertilization reduction induces a loss in overall production (considering marketable fruits) although the difference is not significant, but it is a significant reduction if considering marketable and non-marketable fruits. However, the addition of the inocula partially restored the production rate. This finding is in line with what has been previously reported in the literature [29] and underlines how the nutrient solubilization action operated by microorganisms improves plant nutrition, and thus, its production performance, as well. BER (blossom-end rot) is a physiological disorder usually correlated with a lack of calcium in the plant that may be due to low calcium levels in the soil, or it occurs when there are wide fluctuations in soil moisture, and the plant's ability to take up calcium from the soil is reduced. The application of biostimulants was able to partially reduce the percentage of BER compared to CRD. Among the treatments, the lower positive impact was done by the simultaneous application of the microbial consortia and the commercial inoculum Micomix.
The experiment was carried out in a field usually used for the cultivation of horticultural plants, a field that naturally had a high basal alpha diversity, as shown by the number (476) of the observed genera. The biodiversity indices (Shannon's and Simpson's) can also be considered very high, about 5.2 and 0.98, respectively; in fact, in natural conditions, Shannon's diversity index (H) ranges from 1.5 to 3.5, and it rarely reaches 4.5, while Simpson's index is a probability, with a range from 0 to 1 [35,36]. The addition of the bacterial and Micomix lead to a significant reduction of Shannon's and Simpson's biodiversity indices (within each considered community), a reduction that could be attributed to the selective driver effect of the species present in the inoculum. Although in literature it is not reported that the inoculation of bacterial and fungal-based biostimulants can induce a selective effect on native microbial communities in the soil, it is known that AM fungi can alter PGPB communities by nutrient competition [37]. Moreover, bacteria associated with mycorrhizal mycelium can behave as mycorrhizal helpers and interact with both the bacterial and fungal communities in rhizosphere soil. In particular, B. amyloliquefaciens is reported to behave as a helper of mycorrhization by Xie and coworkers [38]. AM fungi also work synergistically with both symbiotic and free-living nitrogen-fixing bacteria [37,39]. In fact, it has been reported that double inoculation of AM fungi and nitrogen-fixing bacteria induces an increased degree of mycorrhization in spinach [39]. This finding is also confirmed by the results obtained in this work in which the combined inoculation of bacteria and Micomix induces a significantly higher degree of mycorrhization than controls (having low degree of colonization) and fungal inoculum alone, at t1. This result was different (M% comparable to control) in the second sampling, corresponding to the ripening stage. The low degree of AM colonization measured in tomato roots in this experiment could depend on two factors. Firstly, relatively high levels of N and P occurring in the soil before transplanting are known to negatively affect the AM symbiosis establishment [40]. Secondly, fruit production and ripening represent a carbon sink for the plant, which results in a reduction of the available carbohydrates for the fungal partner (thus leading to reduced colonization). These findings were previously hypothesized in tomato plants by Bona and coworkers [28,29] in plants grown in open-field conditions, similar to those used for the present experiment [28,29].
Beta diversity analysis, which describes the degree of divergence between the different analyzed microbial communities, showed that the changes in the genera were significant with respect to all the considered factors (label, time and treatment). The data showed a clear effect of the plant on the composition of the microbial communities ( Figure 5B), which was probably due to the release of root exudates into the soil and also the influence of the time (without considering each treatment) corresponding to the two considered phenological stages [41]. Furthermore, the different administered treatments, with reference to Figure 5C, also lead to an increased diversity among the communities associated with tomato roots. The selective effect highlighted in the analysis of alpha diversity actually leads to a diversification of the communities associated with the inclusion of each inoculum, particularly those composed of Micomix and bacteria (PSBA + MYC).
A specific signature is highlighted by considering the microbial communities associated with the presence of the plant compared to the basal condition (t0). The high soil pH values at t0 (8.29) are associated with the composition in Actinobacteria such as Gaiella, Nocardioides, and Streptomyces, genera normally found in alkaline soils [31]. The reduction in the presence of these genera in the other labels could be associated with a locally induced change in the pH of the substrate due to the addition of inocula, fertilization and the influence of plant root exudates. This hypothesis of the influence of pH shift in determining the observed variations is also concurred in the increase of some genera associated with more acidic pH, such as Acidibacter and Blastocatella [31].
Other genera that are positively stimulated by the presence of the tomato plant belong to the nitrogen-fixing bacteria (reported as legume-nodulating bacteria), such as Allorhizobium, Neorhizobium, Pararhizobium, Rhizobium, Bradyrhizobium, Devosia, Ensifer, and Mesorhizobium. This increase could be attributed to the establishment of the rhizosphere effect induced by the presence of the tomato plant root system [42].
Still associated with the presence of the plant and thus stimulated by the rhizosphere effect, is the genus Variovorax, well known as able to produce and degrade auxins, thus modulating plant growth. Variovorax strains are also able to establish later within communities, since they are more prone to use substrates derived from bacteria instead of plants [43].
The inoculation of bacterial and/or fungal-based biostimulants (B. amyloliquefaciens and P. fluorescens/Micomix) induced significant changes in native microbial populations even though their presence within the microbial communities associated with each treatment is not detectable. This is confirmed by previous studies performed on tomato plants: 43 days after the inoculation of Pseudomonas and Bacillus strains, their presence was not detected. However, plant inoculation with these strains showed significant effects on phosphorus availability and in modulating native bacterial communities across treatments [44]. Considering the signature specifically associated to the introduction of the inocula into the native microbial communities, different genera, belonging to different phyla, were stimulated by all the applied biostimulants (B. amyloliquefaciens, P. fluorescens and Micomix): Pseudomonadota (Alphaproteobacteria-Alsobacter, Amylobacter, Skermanella), Cyanobacteriota (Leptolyngbya), Acidobacteriota (Luteitalea), Actinomycetota (Nakamurella), Bacteroidota (Rhodocytophaga). Luteitalea is the only genus previously reported as stimulated by the presence of B. amyloliquefaciens biofertilizer. In fact, Xue and coworkers reported that B. amyloliquefaciens enhanced the abundance of some genera, such as Vicinamibacter, Brevitalea, Luteitalea, and Desulfonatronum [45].
The other genera that are stimulated under these conditions in the tomato rhizosphere have never been reported to be associated with the introduction of the considered microorganisms into either the tomato rhizosphere or the rhizosphere of other plants of agricultural interest. However, their stimulation turns out to be positive as they are reported to have a beneficial effect on the soil. Alsobacter is reported in the rhizosphere of bok choy as a phytoremediation agent of dibutyl phthalate (DBP), a compound that can be taken up by plants and thus introduced into the food chain [46]. Amylobacter is a potassium-solubilizing microbe [47]. Leptolyngbya increased the defense capacity of tomato plants against tomato bacterial cancer (Clavibacter michiganensis subs. michiganensis) [48]. Rhodocytophaga is a genus often associated with soils with high organic matter content and high salinity [49]. Skermanella can behave as a mycorrhizal helper bacterium, occurring especially where the number of AM fungal propagules is high [50].
The inoculation of the bacterial, fungal and/or their combination inocula results in an inhibition of different genera that were most represented in the controls in the presence of the plant and at baseline without the plant (t0). The genera downregulated are belonging to different phyla: Pseudomonadota (Alphaproteobacteria-Altererythrobacter, Bradyrhizobium, Devosia, Hirschia, Mesorhizobium, Sphingopyxis; Betaproteobacteria-Cupriavidus, Ideonella; Gammaprotebacteria-Pseudoxanthomonas, Tahibacter), Bacillota (Fictibacillus), Verrucomicrobiota (Luteolibacter), Bacterioidota (Ohtaekwangia, Pseudoflavitalea), Actinomycetota (Promicromonospora, Streptomyces), Myxococcota (Sorangium). Several of these genera are dependent by nitrogen availability in soil [51], but nevertheless, the authors believe that their decrease is more to blame for the selective competition effect that may have occurred at the rhizosphere level of tomato plants.

Conclusions
The results belonging to this study highlighted the well-known effect of radical apparatus and its exudates on the native microbiota communities associated with the rhizosphere. Although a high initial biodiversity, shifts in the bacterial community composition occurred and consist mainly in: (1) increase in the abundance of bacterial genera correlated to an acidification of soil, (2) enhanced density of nitrogen-fixing microbes, known for their mycorrhization helping abilities, supported also by efficient mycorrhizal colonization in plants inoculated with the mixed inoculum (PSBA + MYC).
Consequently, the changes mediated by the plant-microbe relationships, both in space and time, can have effects on microbial community structure and activity, nutrient cycling, pH, and finally, on the plant health.
Regarding the effect of bioinocula on the native rhizosphere microbiota, a significant modulation can be observed. The differences between the microbiota composition belonging to each treatment are strongly supported, as reported by the beta-diversity values, and in particular, the co-inoculation of PGPBs and the commercial inoculum Micomix performed better than the other treatments. Overall, a "silent" effect of the bionocula was reported. The bacterial species employed as biostimulants (i.e., Bacillus amyloliquefaciens and Pseduomonas fluorescens) were not found in the analyzed microbiota, as confirmed by other studies [44]. Besides, the genera that were modulated by the addition of the bioinocula belonged to taxonomical group associated with other important agricultural plants [52,53], defining some sort of core microbiome linked to the rhizosphere and directly/indirectly influenced by consortia additions. Funding: This research was funded by Sacco srl., agreement number 040522.

Data Availability Statement:
The genomic sequences were included in the BioProject PRJNA916628, titled "Impact of PGPB bacteria and AM fungi inocula on resident communities associated with tomato roots", available in NCBI database https://submit.ncbi.nlm.nih.gov/subs/sra/SUB1245140 9/overview, accessed on 20 December 2022.

Conflicts of Interest:
The authors declare no conflict of interest.